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Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
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Perspectives in Plant Ecology, Evolution and Systematics
journal homepage: www.elsevier.com/locate/ppees
Research article
Plant size and leaf area influence phenological and reproductive
responses to warming in semiarid Mediterranean species
Enrique Valencia a,b,∗ , Marcos Méndez a , Noelia Saavedra a , Fernando T. Maestre a
a
Departamento de Biología y Geología, Física y Química Inorgánica, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad Rey Juan Carlos,
C/Tulipán s/n, 28933 Móstoles, Spain
b
Department of Botany, Faculty of Science, University of South Bohemia, Branišovská 31, České Budějovice, Czech Republic
a r t i c l e
i n f o
Article history:
Received 13 October 2015
Received in revised form 21 May 2016
Accepted 25 May 2016
Available online 26 May 2016
Keywords:
Climate change
Drylands
Functional group
Functional traits
Open top chambers
Phenology
a b s t r a c t
Changes in vegetative and reproductive phenology rank among the most obvious plant responses to
climate change. These responses vary broadly among species, but it is largely unknown whether they are
mediated by functional attributes, such as size or foliar traits. Using a manipulative experiment conducted
over two growing seasons, we evaluated the responses in reproductive phenology and output of 14
Mediterranean semiarid species belonging to three functional groups (grasses, nitrogen-fixing legumes
and forbs) to a ∼3 ◦ C increase in temperature, and assessed how leaf and size traits influenced them.
Overall, warming advanced flowering and fruiting phenology, extended the duration of flowering and
reduced the production of flowers and fruits. The observed reduction in flower and fruit production with
warming was likely related to the decrease in soil moisture promoted by this treatment. Phenological
responses to warming did not vary among functional groups, albeit forbs had an earlier reproductive
phenology than legumes and grasses. Larger species with high leaf area, as well as those with small
specific leaf area, had an earlier flowering and a longer flowering duration. The effects of warming on
plant size and leaf traits were related to those on reproductive phenology and reproductive output.
Species that decreased their leaf area under warming advanced more the onset of flowering, while those
that increased their vegetative height produced more flowers. Our results advance our understanding of
the phenological responses to warming of Mediterranean semiarid species, and highlight the key role of
traits such as plant size and leaf area as determinants of such responses.
© 2016 Elsevier GmbH. All rights reserved.
1. Introduction
Ongoing global warming is modifying plant vegetative
and reproductive phenology in terrestrial habitats worldwide
(Parmesan and Yohe, 2003; Gordo and Sanz, 2010; Körner and
Basler, 2010). These changes have multiple consequences for
ecosystem structure and functioning, including potential temporal
asynchronies between plants and insects, modification in flower
quality and seed mass, or reduced survival of plants (Goulden
et al., 1996; Walther et al., 2002; Aerts et al., 2004; Williams et al.,
2007; Inouye, 2008; Hegland et al., 2009). Vegetative and reproductive phenological responses to warming have been relatively well
studied in temperate habitats (Dunne et al., 2003; Parmesan and
Yohe, 2003; Sherry et al., 2007; Rollinson and Kaye, 2012), where
∗ Corresponding author at: Departamento de Biología y Geología, Física y Química
Inorgánica, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad
Rey Juan Carlos, C/Tulipán s/n, 28933 Móstoles, Spain.
E-mail address: [email protected] (E. Valencia).
http://dx.doi.org/10.1016/j.ppees.2016.05.003
1433-8319/© 2016 Elsevier GmbH. All rights reserved.
temperature is often a limiting factor for plant growth and development (Parmesan, 2007; Liang et al., 2013). In these areas, both
observational and experimental studies have shown that warming promotes an earlier and longer flowering season (Dunne et al.,
2003; Menzel et al., 2006; Parmesan, 2007; Hovenden et al., 2008;
Kardol et al., 2010).
Phenological studies often show a latitudinal variation in their
responses, with extended growing seasons and a more advanced
flower phenology in warmer compared to milder ecosystems
(e.g., Menzel et al., 2006; Gordo and Sanz, 2009). However, few
experimental studies have been conducted in arid, semi-arid
and dry-subhumid environments (drylands hereafter, sensu UNEP,
1992), particularly when compared to the number of studies conducted in temperate ecosystems (Arft et al., 1999; Wolkovich et al.,
2012; but see Liancourt et al., 2012). This is a worrying knowledge
gap because drylands occupy ∼41% of the Earth’s surface (Safirel
and Adeel, 2005), are a key biome for global plant diversity (White
and Nackoney, 2003), and are currently threatened by climate
change and desertification (Reynolds et al., 2007; Maestre et al.,
32
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
2012). In addition, the phenological impacts of warming in drylands
are likely to differ from those observed in temperate ecosystems.
In water-limited environments, warming could advance flowering,
but may decrease both the number of flowers/fruits and seed mass
(Liancourt et al., 2012) due to reductions in soil moisture (Luo et al.,
2001; Peñuelas et al., 2004).
Despite the large body of literature on phenological responses
to warming, we do not fully understand why observed responses
differ so widely across species (Arft et al., 1999; Peñuelas et al.,
2002). To address this variability, such responses have been studied in relation to factors such as soil moisture, vernalization or
photoperiod (Partanen et al., 1998; Boss et al., 2004; Turck et al.,
2008; Körner and Basler, 2010). Clear connections between flowering time and advances in flowering phenology induced by warming
have been found only in some cases (Fitter et al., 1995; Peñuelas
and Filella, 2001; Root et al., 2003; but see Liancourt et al., 2012;
Whittington, 2012). Plant functional groups, i.e. sets of species
that encompass a variety of common functional attributes (Díaz
and Cabido, 1997; Gitay and Noble, 1997), allow generalizing
how species respond to environmental changes (Wilson, 1999).
For example, annual grasses have an earlier flowering time than
forbs (Cleland et al., 2006). Sherry et al. (2007) showed that earlyflowering species showed an advancement of flowering in response
to warming, while late-flowering species did the opposite. However, no previous studies have evaluated whether the same pattern
applies to early- or late-flowering functional groups. Changes in the
flowering time with warming could modify the coexistence of different species or functional groups within plant communities (i. e.
phenological complementarity; Rathcke and Lacey, 1985).
Plant functional traits can shed light on the responses of reproductive phenology to warming, but their influence has received
little attention so far (Bolmgren and Cowan, 2008; Miller-Rushing
et al., 2008; Richardson et al., 2010). For instance, plant size should
correlate with flowering onset (Vile et al., 2006), but its relationship
with other reproductive phenological variables is unknown. Thus,
a better knowledge about the links between functional traits and
phenological responses is needed to enhance our ability to predict
plant responses to warming.
To fill current gaps in our understanding about the responses
of Mediterranean semiarid species to climate change, we experimentally evaluated the reproductive phenology and reproductive
output to warming of 14 Mediterranean semi-arid species belonging to different functional groups. Specifically, we assessed: (1) how
warming affects key phenological events, such as flowering (onset,
peak, cessation or duration) and fruiting (onset, peak), and reproductive output (number of flowers, fruits or seed mass), (2) whether
responses to warming were consistent among the different reproductive phenology and reproductive output variables, and between
years with contrasting environmental conditions, (3) the role of
functional groups and functional traits on reproductive phenological responses, and how warming modifies them, and (4) whether
the magnitude of intraspecific changes in functional traits modulate these responses to warming. We predict that warming would
cause an advance of all components of reproductive phenology,
an increase in flowering duration and a decrease in the number
of flowers, fruits and seed mass (Liancourt et al., 2012). Warming will also result in less water availability compared with the
control, and these differences will be especially marked at the end
of the growing season (Valencia et al., 2016b). As a consequence,
reproductive output might decrease with warming (Liancourt et al.,
2012). We also hypothesized that phenological responses to warming will vary among plant functional groups (Cleland et al., 2006),
and that these responses will be affected by functional traits such
as plant size and leaf area (Vile et al., 2006; Sherry et al., 2007;
Bolmgren and Cowan, 2008).
2. Materials and methods
2.1. Study species
We studied 14 species belonging to three broad taxonomical functional groups: grasses (Cynodon dactylon [L.] Pers., Poa
pratensis [L.], Agropyron cristatum [L.] Gaertn., Festuca ovina [L.]),
nitrogen-fixing legumes (Hedysarum coronarium [L.], Dorycnium
pentaphyllum [Scop.], Anthyllis vulneraria [L.], Medicago sativa [L.],
Bituminaria bituminosa [L.] C.H. Stirt.) and forbs (Plantago lanceolata [L.], Sanguisorba minor [Scop.], Echium boissieri [Steud.], Echium
plantagineum [L.], Asphodelus fistulosus [L.]; Table S1). We selected
these species because they typically coexist in grassland communities, abandoned fields and roadside slopes undergoing secondary
succession in semi-arid Mediterranean areas (García-Palacios et al.,
2010).
2.1.1. Experimental design
A microcosm experiment was conducted at the Climate Change
Outdoor Laboratory, located at the facilities of Rey Juan Carlos University (URJC, Móstoles, Spain: 40◦ 20 37 N, 3◦ 52 00 W, 650 m a.s.l.)
between April 1, 2011 and July 31, 2013. Microcosms consisted
of plastic pots (depth 38 cm, internal diameter 28 cm) filled with
32 cm of natural soil (sand content: 73.5%, silt content: 18.5%, clay
content: 8.0%) and 3 cm of expanded clay for drainage at the base.
All the microcosms were initially watered with 500 mL of a soil
microbial inoculum to recreate realistic microbial communities, as
described in Maestre et al. (2005). All the pots were placed in holes
in the ground, and kept under ambient light and rainfall to keep the
most natural conditions.
The experiment was designed as a randomized block design,
with two treatments: warming (control vs. ∼2.9 ◦ C annual temperature increase), and functional group (three levels: grasses,
nitrogen-fixing legumes and forbs). Microcosms were arranged in
four blocks containing a replicate of species per temperature treatment, resulting in 112 microcosms in total. A minimum distance
between microcosms of 1 m was established to minimize the risk
of sampling non-independent areas.
Seeds for this experiment were obtained from commercial
sources (Intersemillas Ltd., Valencia, Spain). In April 2011, we randomly sowed seeds of each species within each microcosm. We
planted a monoculture in each microcosm at a density of 160
individuals/m2 . This density is within the range found in semiarid
ecosystems from central Spain (e.g., 131 individuals/m2 ; ChacónLabella et al., 2016). The microcosms were watered with 1 L three
times per week during the first six weeks of the experiment, and
once a week in July and August 2011, to ensure seed establishment. Weeds were regularly removed during the experiment. The
warming treatment was set up on December 05, 2011, once all
microcosms had an established population, and the experiment terminated in July 2013. We elevated the temperature in the warming
treatment by using open top chambers (OTCs), which have been
commonly employed in warming experiments (e.g., Marion et al.,
1997; Hollister and Weber, 2000; Escolar et al., 2012; Liancourt
et al., 2012). These were hexagonal chambers built of methacrylate
plates, with sloping sides of 65-52-42 cm (Fig. S1). Methacrylate has
high transmittance in the visible spectrum (92%), very low emission
of the infrared wavelength (4%) and high energy transmission (85%;
data provided by the supplier, Decorplax Metacrilatos S.L., Madrid,
Spain). Chambers were open on their top to allow rainfall and air
flow, and were raised 5 cm from the soil surface to achieve adequate
air flow and avoid excessive heating. Air temperature and humidity were measured in warming and control plots using automated
sensors (HOBO U23 Pro v.2 Temp/RH, Onset Corporation, Bourne,
MA, USA). The OTCs employed raised temperature by an average
of ∼2.9 ◦ C compared to control plots during our experiment (Fig.
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
S2b). This temperature increase was consistent with the predictions of climatic models for the study area, ranging from 2 to 4 ◦ C
by the second half of the twenty-first century (RCP 8.5 scenario,
Intergovernmental Panel on Climate Change (IPCC, 2013).
2.1.2. Phenological and plant sampling
Flowering phenology and flower and fruit production in all
the plants of each microcosm were scored every two-three days
throughout the spring flowering period (from March to early July) of
2012 and 2013. All inflorescences or infructescences were counted
in all plants of each microcosm in each census. We focused on the
spring flowering because most species only bloomed in this period.
From the raw counts we calculated the following phenological variables: dates of onset, peak and cessation of flowering, flowering
duration, maximal number of flowers or inflorescences produced
at the flowering peak (flower production hereafter), fructification
onset and peak, maximal number of fruits or infructescences produced at fructification peak (fruit production hereafter) and seed
mass. Flowering onset, peak and cessation were defined as the
number of days elapsed between the 1st of March and the first
flower, maximal number of flowers and end of blooming, respectively. A few outlier flowers opening very early or very late during
the flowering period were excluded from these calculations. Flowering duration was estimated as the difference between flowering
onset and cessation. Accordingly, we measured the onset and peak
of fructification as the number of days elapsed between the 1st
of March and the date when the first fruit and the highest number of fruits were recorded, respectively. Seed mass was estimated
by weighing a sample of twenty seeds per microcosm; seeds were
collected when plants had ripe fruits at the end of the fructification
period of 2013. We did not collect seeds in 2012 to avoid altering
the establishment and growth of new plants in the microcosms.
Phenological measurements were gathered on twelve species during 2012 (Fig. 1). Festuca ovina and E. boissieri did not flower in 2012,
but did so in 2013. Poa pratensis and H. coronarium suffered from
severe mortality under warming during the summer of 2012, and
were dropped from the analysis in 2013.
We visually estimated total cover (TC, cm2 ) as the area occupied
by plants in each microcosm. We also measured the following traits
according to standard protocols (Cornelissen et al., 2003): vegetative height (VH, cm), leaf area (LA, cm2 ), leaf length (LL, cm), leaf
width (LW, cm), leaf thickness (LT, mm), specific leaf area (SLA,
cm2 g−1 ) and leaf dry matter content (LDMC, g g-1). These traits
were selected because they indicate different plant species strategies for acquiring, using and conserving resources, such as light,
nutrients and water (Westoby et al., 2002; Wright et al., 2004).
Trait measurements were conducted in May 2012 and June 2013 in
a randomly chosen individual per microcosm. Additionally, we also
measured the number of individuals and the volume (calculated as
VH × TC) occupied by each population. Volume was considered as a
good proxy of aboveground biomass, as both variables were highly
correlated (r = 0.82 P <0.001, n = 92) at the end of the experiment.
2.2. Statistical analyses
2.2.1. Functional trait classification
As many of the traits measured are correlated among them
(Table S2), we reduced our original list of nine traits by means of
a principal component analysis (PCA) performed across all species
using the mean trait values for each microcosm. This approach is
based on selecting one trait for each PCA component as a functional marker representative of each axis of specialization (Garnier
et al., 2004). These values were log-transformed prior to PCA analyses. We selected three independent PCA components to identify
the main axes of specialization among species, which together
explained around 80% of the total variance found in the data (Table
33
S3). These analyses were carried out separately for each sampling
year. The first, second and third PCA components were highly
related to plant size (VH, TC and volume), leaf size (LA, LT and
LL) and leaf morphology (SLA), respectively, during the two study
years (Table S3). To represent each axis of variation, we selected
traits strongly correlated with each PCA component that were
not strongly correlated (r < 0.15) with the remaining traits (Tables
S2 and S3). These traits, selected to represent each independent
axis in further analyses, were VH, LA and SLA. This procedure has
the advantage of considering only independent traits in further
analyses, and allows us to identify important traits that reflect independent functional niche axes (Gross et al., 2007; Butterfield and
Suding, 2013).
2.2.2. Responses of reproductive phenology and reproductive
output to warming
We used General Linear Mixed Models (GLMM) to assess the
responses to warming of six phenological variables (onset, peak,
duration and cessation of flowering and onset and peak of fructification) and three reproductive output variables (seed mass, flower
and fruit production) separately for each year. In all models, warming, functional group and their interaction were considered as fixed
factors, whereas block and species, nested within functional group,
were considered as random factors. We included VH, LA, SLA and
the number of individuals per microcosm as covariates, as well as
the interactions between warming and VH, LA, and SLA in our models. Seed mass, flower and fruit production, number of individuals
and all the traits were log-transformed prior to GLMM analyses
to improve their normality. We used a stepAIC procedure (Grace,
2006) to evaluate the relationships of each factor and covariate
with phenological and reproductive variables, and selected the
best model based on the Akaike Information Criterion (AIC; Akaike,
1973). When significant responses among functional groups were
found, we conducted a Tukey post-hoc analysis to evaluate differences among them.
We quantified the effect of warming on leaf/size traits
and phenological variables using the RII index, calculated as
(Xamb − Xwar )/(Xamb + Xwar ), where Xamb and Xwar are the values of
each variable in the control and warming treatments, respectively
(Armas et al., 2004). This index ranges from −1 to +1. Negative values indicate an increase of the variable considered (or a delay in the
case of phenological events) under warming, while positive values
indicate the opposite. Relationships between changes in leaf and
size traits and changes in reproductive phenological responses, as
measured with the RII index, were assessed using linear regression.
All statistical analysis were carried out with R (R Development
Core Team, 2012), using the packages “lme4” (Bates et al., 2014)
and “multcomp” (Hothorn et al., 2008). The raw data used in our
analysis are available from figshare (Valencia et al., 2016a).
3. Results
The two years studied had contrasting environmental conditions (Fig. S2a). The first year (2012) was warmer and drier (14.5 ◦ C
and 141 mm of mean temperature and precipitation during the
growing season, respectively) than the second year (2013; 13.6 ◦ C
and 229 mm of mean temperature and precipitation during the
growing season, respectively). On average, our warming treatment
increased air temperatures by 3.3 ◦ C and 2.6 ◦ C during the growing
seasons of 2012 and 2013, respectively.
3.1. Effects of warming on flowering and fruiting phenology
Trends in phenological responses were consistent across years
except for the cessation of flowering, where results were highly
34
2012
Treatment
Warming (W)
Functional group (FG)
VH
LA
SLA
N◦ ind
W × FG
W × VH
W × LA
W × SLA
OFL
PFL
FLD
CFL
est
␹
P
est
␹
P
est
␹
P
est
␹
1
2
1
1
1
1
2
1
1
1
−7.5
12.880
11.458
15.892
<0.001
0.003
<0.001
−1.8
0.371
4.936
0.543
0.085
4.3
15.047
<0.001
0.089
0.006
0.003
0.013
−4.1
6.4
2.896
10.235
8.725
6.182
4.765
10.519
5.796
17.561
4.697
0.096
−6.2
2
5.7
5.5
2
−3.8
8.4
PFR
OFR
d.f.
2
2
P
est
␹
P
est
␹2
P
0.029
0.005
0.016
<0.001
−2.1
6.479
12.263
0.011
0.002
−1.6
1.540
6.474
0.207
2.396
1.705
1.218
0.215
0.039
0.649
0.122
0.192
0.270
4.560
0.033
2.121
0.145
−1.3
2
2.949
0.086
−0.6
1.7
−1.3
−0.9
2013
Treatment
Warming (W)
Functional group (FG)
VH
LA
SLA
N◦ ind
W × FG
W × VH
W × LA
W × SLA
OFL
CFL
d.f.
est
␹
1
2
1
1
1
1
2
1
1
1
−6.1
14.782
23.307
64.112
1.928
6.626
26.25
−11.4
1.9
4.2
−6.7
2
4.452
2.944
FLD
PFL
OFR
PFR
P
est
␹
P
est
␹
P
est
␹
P
est
␹
P
est
␹2
P
<0.001
<0.001
<0.001
0.165
0.010
<0.001
3.8
1.666
2.538
0.197
0.281
10.3
0.431
0.035
<0.001
0.120
0.041
0.068
5.041
0.025
−2.7
5.908
0.015
1.3
2.264
0.132
<0.001
0.097
0.620
6.731
12.998
2.425
4.166
3.320
−2.1
13.536
2.757
−1.8
6.196
0.013
3.988
0.136
0.001
0.057
<0.001
0.059
0.421
0.004
0.057
−1.9
6.2
3.5
10.715
5.727
25.386
3.567
0.646
8.140
5.720
2.284
0.131
2.389
0.122
8.955
3.414
0.003
0.065
0.035
0.086
2
10.7
4
−2
5.4
2
−8.2
2.9
4.3
−3.6
2
2
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
Table 1
Summary results of the General Linear Mixed Models (GLMM) evaluating the effects of warming, functional groups, functional traits and their interactions on the phenological events measured in 2012 and 2013. OFL: onset of
flowering; CFL: cessation of flowering; FLD: flowering duration; PFL: peak of flowering; OFR: onset of fructification; PFR: peak of fructification; VH = vegetative height, LA = leaf area; SLA = specific leaf area; N◦ ind = number of
individuals per microcosm.
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
35
Fig. 1. Flowering phenology of the species studied during the growing seasons of 2012 and 2013. OFL: onset of flowering; PFL: peak of flowering; CFL: cessation of flowering.
Data represent means ± SE at the beginning and end of flowering phenology (n = 4 of each species in warming or control).
species-specific (Fig. 1). In both years, the magnitude of the phenological change by warming was higher for the onset of the
flowering, compared to the flowering peak or the cessation of flowering (Table 1). In the drier year, warming promoted a significant
earlier onset and peak of flowering, and an earlier fruiting onset
(P < 0.05, Table 1). We also found a marginally significant trend
towards a longer duration of flowering with warming (P = 0.09,
Table 1). In the wetter year, warming led to an earlier flowering
and fruiting onset, to an earlier fruiting peak of fruiting, and to a
longer flowering duration (P < 0.05, Table 1).
Functional group significantly affected flowering variables in
both years, and fructification variables in the drier year (Table 1,
Fig. 2). The phenology and duration of flowering were earlier and
longer in forbs than in grasses and nitrogen-fixing legumes in
both years (Fig. 2). The same occurred with fruiting phenology
variables, but differences were significant only in the drier year
(Table 1, Fig. 2). There were no differences between grasses and
nitrogen-fixing legumes in any of the flowering and fruiting variables measured (Fig. 2). The interaction between warming and
functional group was not significant for any variable (Table 1).
Leaf and size traits affected flowering and fructification in both
years (Table 1). Larger plants had an earlier onset and peak of flowering, and a longer flowering duration in both years (Table 1). Plants
with a higher LA had a later date of cessation of flowering in both
years, a later peak of flowering and a larger flowering duration in
the drier year and an earlier onset of fructification in the wetter
year (Table 1). A smaller SLA promoted an earlier onset and peak of
flowering, but only in the wetter year. In the drier year, plants with a
lower vegetative height in the warming treatment had a significant
earlier peak of fructification (warming × VH interaction; Table 1,
Fig. S3a). Plants with a higher LA in the control treatment had a significant longer flowering duration in the wetter year (warming × LA
interaction; Table 1, Fig. S3c).
The analyses of RII values showed that, in the drier year,
decreases in LA under warming correlated with an advanced peak
of flowering (Fig. S4). In the wetter year, species that decreased
their LA under warming advanced more the onset of flowering than
species with the opposite trait response (Fig. S5).
3.2. Effects of warming on reproductive variables
Warming significantly decreased flower and fruit production
only in the wetter year (P < 0.05, Table 2). Fruit production in forbs
was higher than in grasses and legumes in both years (Fig. 2;
Table 2). VH was positively correlated with flower and fruit production in both years (Table 2). In the drier year, increases in LA
increased flower production (Table 2). Seed mass increased with
increases in LA but decreased with increases in SLA (Table 2).
Additionally, species that increased VH in response to warming
produced more flowers (Fig. S5).
4. Discussion
4.1. Flowering and fruiting responses to warming
In agreement with our hypothesis, warming advanced the onset
of flowering, and the onset and peak of fructification; it also
increased the duration of flowering throughout the experiment
(Table 1). These results qualitatively agree with previous observational and manipulative studies conducted around the world
(Fitter and Fitter, 2002; Peñuelas et al., 2002; Matsumoto et al.,
2003; Gordo and Sanz, 2009). In our experiment, the onset of
flowering was the variable most affected by warming, as some
species advanced their flowering up to 20 days in this treatment
(Table S4). Previous observational studies have found that warming commonly advances the onset of flowering by three days in
northeast North America or four days in England (Fitter et al.,
1995; Miller-Rushing et al., 2008; Miller-Rushing and Primack,
2008). However, the large advance observed in the onset of flowering due to warming is comparable to observational studies in
Mediterranean ecosystems (Gordo and Sanz, 2009), and to another
manipulative study conducted in subarctic areas (Aerts et al., 2004).
We suggest that the onset of flowering had a higher response to
warming compared to the rest of phenological variables because
36
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
2012
100
2012
2013
a) onset of flowering
140
Julian day
a
a
120
a
110
b
b
20
90
0
80
c) peak of flowering
80
ab
a
a
a
a
a
a
a
0
e) onset of fructification
130
130
120
a
a
a
ab
100
90
a
Julian day
140
f) peak of fructification
a
120
a
110
a
a
a
a
100
90
b
80
80
g) flower production
3
2
a
a
a
a
a
a
0
Number of fruits (log transf)
Julian day
b
ab
140
Number of flowers (log transf)
d) flowering duration
20
40
1
a
40
a
b
60
110
a
a
a
60
100
80
a
a
100
Days
Julian day
ab
40
120
b) cessation of flowering
130
80
60
2013
3
h) fruit production
2
b
b
a
1
ab
a
a
0
Gr
Le
Fo
Gr
Le
Fo
i) Seed mass
mg (log transf)
5
4
a
3
a
a
2
1
0
Gr
Le
Fo
Gr
Le
Fo
Fig. 2. Phenological and reproductive variables for each functional group. Significant differences among functional groups are indicated by different letters (Tukey post-hoc,
P < 0.05). Gr: grasses; Le: nitrogen-fixing legumes; Fo: forbs. Data represent means ± SE (n = 96).
it happens during the first stages of the growing season, when
temperature, but not water, could be a factor limiting plant development (Fig. S6). Our results increase our knowledge regarding
flowering and fruiting responses of semiarid Mediterranean species
to warming, and could have important ecological implications. For
instance, the large advances in flowering of some species could
promote dramatic ecological asynchronies between neighboring
plants (Price and Waser, 1998) or between them and their pollinators or herbivores (Williams et al., 2007), which could lead to
changes in the composition or abundance of rural communities
(Walther et al., 2002) in drylands.
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
37
Table 2
Summary results of the Linear Mixed Models evaluating the effects of warming, functional groups, functional traits and their interactions on the flower production (FLP),
fruit production (FRP) and seed mass in 2012 and 2013. VH = vegetative height; LA = leaf area; SLA = specific leaf area; N◦ ind = number of individuals per microcosm.
2012
Treatment
FLP
Warming (W)
Functional group (FG)
VH
LA
SLA
N◦ ind
W × FG
W × VH
W × LA
W × SLA
FRP
d.f.
est
␹
1
2
1
1
1
1
2
1
1
1
−0.11
3.304
0.069
0.36
0.17
48.348
7.011
<0.001
0.008
2
P
est
␹2
P
0.38
13.834
17.909
<0.001
<0.001
2013
Treatment
Warming (W)
Functional group (FG)
VH
LA
SLA
N◦ ind
W × FG
W × VH
W × LA
W × SLA
FLP
FRP
Seed mass
d.f.
est
␹
P
est
␹
P
1
2
1
1
1
1
2
1
1
1
−0.19
0.016
0.095
<0.001
0.907
−0.31
0.54
−0.01
5.799
4.709
51.497
0.014
8.597
11.225
20.935
3.392
0.003
0.004
<0.001
0.066
0.14
4.158
0.041
2.556
0.110
2.660
0.103
2
4.2. Reproductive responses to warming
As predicted by our hypothesis, warming reduced flower and
fruit production in the studied species. This was probably due to
the reduction in soil moisture promoted by warming (Fig. S6).
Decreases in soil moisture in this treatment were particularly
important at the end of the growing season, where water is scarce
and only the largest species could stand these stressful conditions
(Tsakaldimi et al., 2012; Villar-Salvador et al., 2013).
The reduction in the reproductive output observed could be also
explained by changes in vegetative size under warming (Fig. S5). For
instance, these changes could be related with faster plant development throughout the growing season (Springate and Kover, 2013).
Another possibility is that reproductive output was indirectly
affected by changes in the vegetative and flowering phenology.
There are two contrasting scenarios about the relationship between
vegetative phenology and flower and fruit production. First, a positive relationship between advances in vegetative phenology and
reproductive output could occur if species that advance their leaf
phenology under warming also increase their vegetative size, as
larger plants usually enhance their fitness (Cleland et al., 2012;
Springate and Kover, 2013). Thus, larger vegetative size could occur
if increases in the length of the growing period last longer than
increases in flowering duration. Second, a negative relationship
between advances in vegetative phenology and reproductive output could occur if an earlier onset of flowering involves a reduced
allocation of resources to growth, a smaller size, and therefore a
reduction of resources available for reproduction (Bolmgren and
Cowan, 2008). In the first scenario, we expect that species could
accumulate more biomass in these situations (Hollister et al., 2005;
Cleland et al., 2012), a response that would lead to more flowers
and fruits, and to larger seeds. Previous studies have observed this
phenomenon in temperate ecosystems, where warming increased
flower and fruit production and seed mass (Hollister and Weber,
2000; Lemmens et al., 2008; Springate and Kover, 2013). In our
study, species advanced their flowering but only some species
0.38
0.17
2
est
␹2
P
0.12
−0.12
0.07
11.44
5.272
3.880
<0.001
0.022
0.049
increased their plant size, being these changes related to changes
in flower production (Fig. S5). Further research is required to evaluate how warming responses of vegetative and flowering season
length influence plant growth, and how these relationships are
related to the reduction in number of flowers and fruits showed
in Mediterranean semiarid ecosystems.
4.3. Phenology varies among functional groups
Considering functional groups could potentially help to predict
community responses to global change. For example, experiments
manipulating variables such as CO2 , N deposition or grazing found
differential flowering responses among functional groups (Cleland
et al., 2006; Spence et al., 2014). In our case, although reproductive phenology varied consistently among plant functional groups,
these differences did not translate into early- flowering functional
groups having a significantly higher advancement in their flowering
variables with warming than late-flowering functional groups. This
contrasts with the results of Sherry et al. (2007), possibly because
the species we studied flowered in spring and not across all seasons,
as those in that study. Instead, species-specific flowering responses
not related to functional groups were found, as in other studies
(Hollister and Weber, 2000; Fitter and Fitter, 2002; Liancourt et al.,
2012). Our results suggest that functional groups do not seem to
provide enough resolution to address plant responses to warming.
4.4. Functional traits affect phenological responses
The axes of specialization represented by size and leaf traits
provided different information than that supplied by functional
groups (Fig. S7). The selected traits are surrogates of basic functional properties of plants (Westoby et al., 2002). Plant size is a
good surrogate for water use efficiency and/or competitive ability
(Westoby et al., 2002; Cornelissen et al., 2003). Leaf area is related to
light interception and absorption, resource allocation, water uptake
strategy and water stress tolerance (Westoby et al., 2002; Gross
38
E. Valencia et al. / Perspectives in Plant Ecology, Evolution and Systematics 21 (2016) 31–40
et al., 2007). SLA indicates plant relative growth rate and resource
capture and utilization (Wright et al., 2004), and is a descriptor
of dominant plant strategies (Westoby et al., 2002); for instance
higher SLA is related with fast-growing strategy (Freschet et al.,
2011). The functional traits measured influenced reproductive phenology and/or reproductive output. Larger species with small LA
and SLA had an earlier flowering phenology and longer flowering
duration (Table 1). An expanded flowering period could increase
the capacity of these species to adapt to warming. In addition, the
production of flowers and fruits varied with plant size, while LA
and SLA influenced seed mass in opposite directions (Table 2). We
speculate that the observed relationships between larger plant size
and an earlier flowering can be explained if the stored resources
(acquired during previous growing seasons) are more important
than resources acquired during the current season, as suggested by
Bolmgren and Cowan (2008). Our findings advance our understanding of the responses of reproductive phenology in Mediterranean
semiarid species at an interspecific level. Further research is needed
to test whether observed responses can be found with other nonherbaceous perennial species (e.g. shrubs or trees; Bolmgren and
Cowan, 2008).
The interactions between plant size/leaf area and warming
found indicate that these traits influenced the response of the
phenological and reproductive variables to warming. The peak of
fructification was delayed for plants with higher VH under warming compared to what we found in the control treatment (Fig. S3a).
In addition, flowering duration was higher in species with higher
leaf area in the control treatment, an effect that vanished under
warming (Fig. S3b). We thus believe that the explicit consideration
of functional traits can help us to predict which species will be more
affected by warming, and hence deserve more attention by future
research on this topic. We must note that the functional traits were
also modified by warming, as revealed by the RII analyses (Figs. S4
and S5). Thus, warming induced changes in traits that, in turn, could
influence the phenological and reproductive responses to warming. For instance, decreases in LA by warming advanced more the
onset and peak of flowering (Figs. S4 and S5), so changes in LA were
coupled with changes in flowering phenology of the species studied. Furthermore, species that under warming increased their VH
had higher flower production compared to those with no change
or decreased VH (Fig. S5).
Our findings indicate that increases in size can be a way to mitigate the negative effects of warming on flower and fruit production.
Plants could respond to environmental variability by plasticity in
functional traits (Sultan et al., 1998). The phenotypic response in
our plant traits might be plastic (Berteaux et al., 2004; Pigliucci,
2005; Nicotra et al., 2010), but we cannot rule out genetic differences. Nevertheless, the plant size/leaf area changes detected were
species-specific (Yamori et al., 2009; Gunderson et al., 2010) and
essential to withstand changing climate conditions. Morphological and physiological adaptations to mitigate the effects of climatic
conditions have been documented (Gianoli and González-Teuber,
2005; García-Verdugo et al., 2009). The degree to which whole plant
communities are affected by warming will depend, to a large extent,
on the ability of their constituent species to acclimate (sensu Smith
and Dukes, 2012) to these climatic conditions. Our results highlight the interest of incorporating intraspecific trait variability into
models aiming to predict changes in species distributions under different climate change scenarios (Valladares et al., 2014). The ability
of species to modify key functional traits (through plastic responses
or filtering of genotypes) could be decisive for their future under
warming, especially under the more variable climate expected in
drylands (Beniston et al., 2007). The study of these parallel changes
could anticipate how Mediterranean semiarid species can respond
to ongoing climate change.
Acknowledgements
We thank V. Ochoa, B. Gozalo, and M. Berdugo for their help
during the phenological measurements. This research was funded
by the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant
agreement 242658 (BIOCOM). F.T.M. acknowledges support from
the Salvador de Madariaga program of the Spanish Ministry of Education, Culture and Sports (PRX14/00225) during the writing of the
manuscript.
Appendix A. Supplementary data
Supplementary data associated with this article can be found,
in the online version, at http://dx.doi.org/10.1016/j.ppees.2016.05.
003.
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